Triple

T33496951

Position	Surface form	Disambiguated ID	Type / Status
Subject	Tram line 4 (Budapest)	`E857886`	entity
Predicate	connectsToMetroLineAt	`P199130`	FINISHED
Object	M3 at Nyugati tér M3 at Nyugati tér is a major station on Budapest’s M3 (blue) metro line, serving as an important interchange point beneath the central Nyugati railway and tram hub.	`E2052680`	NE FINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini

Instruction

Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).

Input

Phrase: M3 at Nyugati tér | Statement: [Tram line 4 (Budapest), connectsToMetroLineAt, M3 at Nyugati tér]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: M3 at Nyugati tér
Triple: [Tram line 4 (Budapest), connectsToMetroLineAt, M3 at Nyugati tér]

Generated description

M3 at Nyugati tér is a major station on Budapest’s M3 (blue) metro line, serving as an important interchange point beneath the central Nyugati railway and tram hub.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: connectsToMetroLineAt
Context triple: [Tram line 4 (Budapest), connectsToMetroLineAt, M3 at Nyugati tér]

A. subwayLine
Indicates that there is a subway line connection or service relationship between the referenced entities.
B. metroLineCode
Indicates the specific code or identifier assigned to a metro (subway) line with which an entity is associated.
C. servedByTramwayLine
Indicates that a location or area is provided public transport service by a specific tramway line.
D. metroLineInaugurated
Indicates that a metro line was officially opened and began operation on a specific date or during a specific event.
E. subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
F. None of above. chosen

Provenance (7 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step	Stage	Batch ID	Status	When
creating	Elicitation	`batch_69f3497660508190a541826a81f7e9ab`	completed	April 30, 2026, 12:22 p.m.
NER	Named-entity recognition	`batch_69ff21cbd9108190a52c0ba42004c669`	completed	May 9, 2026, noon
NED1	Entity disambiguation (via context triple)	`batch_6a3595bf90fc81908e34a50024ca94ac`	completed	June 19, 2026, 7:17 p.m.
NEDg	Description generation	`batch_6a3596afcad88190891d62137b93e1bb`	completed	June 19, 2026, 7:21 p.m.
NED2	Entity disambiguation (via description)	`batch_6a35972e0a908190b5e85121a47577a3`	completed	June 19, 2026, 7:23 p.m.
PD	Predicate disambiguation	`batch_69ff1faea91881908c626c70bca5100a`	completed	May 9, 2026, 11:51 a.m.
PDg	Predicate description generation	`batch_69ff21ca6964819088bdf1810b7863f2`	completed	May 9, 2026, noon

Created at: May 1, 2026, 1:38 a.m.